Optimizing Resource Allocation by Computer Vision

ABSTRACT

It is provided a method, including providing location information indicating a location of a terminal to a radio-independent localization and tracking system; evaluating at least one of environmental information and tracking information received from the radio-independent localization and tracking system with respect to the terminal in response to providing the location information; managing a resource for serving the terminal based on the at least one of the environmental information and the tracking information, wherein the environmental information includes information about an environment of the terminal, and the tracking information includes information about a track of the terminal.

FIELD OF THE INVENTION

The present invention relates to using information from a computervision system to optimize resource allocation of a terminal (UE).

Abbreviations

3GPP 3^(rd) Generation Partnership Project

3G/4G/5G 3^(rd)/4 ^(th)/5 ^(th) Generation

ACK Acknowledged

A-GNSS Assisted Global Navigation Satellite System

AoD Angle of Departure

API Application Programming Interface

BVDM Building Vector Data Map

CAM camera

CN Core Network

CSI Channel State Information

CSI-RS CSI-Reference Signal

CV Computer Vision

DL Downlink

eMBB Enhanced Mobile Broadband

eNB eveloved NodeB

FCC Federal Communications Commission

FOV Field of View

FR Frequency Range

gNB Next generation NodeB

GNSS Global Navigation Satellite System

HO Handover

IAB Integrated Access and Backhaul

ID Identifier

IE Information Element

IIoT Industrial Internet of Things

IP Internet Protocol

ITU-R International Telecommunication Union-Radiocommunication Sector

LMC Location Management Component

LMF Location Management Functionality

LOS Line of Sight

LPP LTE Positioning Protocol

LTE Long-term Evolution

MAC Medium Access Control

MDT Minimization of Drive Tests

MEC Multi-Access Edge Computing

ML Machine Learning

MME Mobility Management Entity

mmW millimetre waves

MRO Mobility Robustness Optimization

NACK Not Acknowledged

NG Next Generation

NR New Radio

OTDOA Observed Time Difference of Arrival

PHY Physical (layer)

QoS Quality of Service

RACH Random Access Channel

RAN Radio Access Network

RAT Radio Access Technology

Rel Release

REM Road Experience Management

RF Radio Frequency

RNA RNSAP User Adaption

RNSAP Radio Network Subsystem Application Part

RRC Radio Resource Control

RRM Radio Resource Management

Rx Receive

SON Self-Optimizing Networks

SSB Synchronization Signal Block

TR Technical Report

TRP Transmission Point

Tx Transmit

UE User Equipment

URLLC Ultra-Reliable and Low-Latency Communications

BACKGROUND OF THE INVENTION

A main driver for UE positioning (i.e. determining the position of theUE) in cellular networks are FCC E911 requirements [1]. In LTE, theinformation on UE position has been considered unknown or known with alow level of resolution. With the introduction of very sensitiveuse-cases like URLLC, 5G-NR needs to ensure that the information on UEposition and location (environment) is known in order to improvemobility, service continuity and quality aspects.

In NR Rel-15, only Cell-ID (with cell portion ID) and RAT-independentsmethods (e.g., A-GNSS) based on LTE LPP were specified. Standalone NRpositioning methods for Rel-16 (especially RAT-dependent techniques)were studied in the RAN1 study item “Study on NR positioning support(Release 16)”. The key findings are summarized in the resulting 3GPP TR38.855: Technical Specification Group Radio Access Network; Study on NRpositioning support (Release 16), v 2.1.0, 2019.

Specification is currently ongoing in the Rel-16 work item “NRPositioning Support” RP-190752, New WID: NR Positioning Support, Intel,RAN #83, March 2019.

RAN2 agreed in the meeting #105 that Location Management functionality(LMF) in NG-RAN is recommended for normative work. RAN Plenary Meeting#83 on March 2019 agreed to start a “Study on local NR positioning inRAN” in Q3 2019. The LMF in NG-RAN is called Location ManagementComponent (LMC).

In practice, accurate positioning plays a key role in 5G NR networks andthe industry is exploiting new data domains for providing thisinformation. The need for improving the network by incorporatingexternal systems as sources of relevant information is becomingparamount and is aligned with emerging topics such as Digital Twins andMirror World concepts. Interaction between radio networks and industrialplatforms is also a key subject of Re1.17 and beyond.

One of the distinctive features of NR is the reliance on sophisticatedbeam steering by highly directive antenna arrays. Although not exclusiveto, continuous and efficient beam tracking is substantiallyindispensable for FR2 bands 257 to 511, commonly referred to asmillimeter waves (mmW).

In NR, positioning is no longer an add-on feature and device trackingrequirements are stricter due to the quasi-optical behavior of mmWwireless links, the beam-centric design, and the foreseen networkdensification, which increases the likelihood of a LOS between UE andthe antenna array but also the number of positioning and mobilityrelated events (HOs, beam reselections, etc.).

Numerous solutions for UE positioning and beamforming in cellularnetworks exist, but they are chiefly based on appropriate radio signalstructure, radio propagation-based measurements and advanced signalprocessing. However, most radio-only solutions suffer from excessivedelays and/or become very intricate when many narrow beams are deployed.Furthermore, these solutions hardly address—with the requiredproactivity and accuracy—the transitions of devices from outdoor toindoor environments (indoor/outdoor, street/train, etc). Furthermore,the availability of wireless communication network may be compromised,e.g. due to lack of UE measurements, unexpected radio interference,unexpected blocking of the communication channel, etc.

Anticipating these changes efficiently is particularly important for MROand SON. MRO adapts the radio resources to the average user mobilityprofile. Thereafter, it is not able to react optimally when the mobilityprofile of a UE differs from the average. The current MRO can optimizethe handover parameters only at the granularity of a cell pair and/or UEgroup, but cannot provide in real-time more detailed knowledge of thevarying number of UEs and their trajectories (e.g. outdoor to indoor).

A survey of the techniques specified for LTE positioning (as well asprevious generations) is found in [6]. Below we list related academicand industrial work:

[1] Federal Communication Commission (FCC), Fourth Report and Order:“Wireless E911 Location Accuracy Requirements”, FCC-15-9, Docket#07-114, 2015. https://www.fcc.gov/document/fcc-adopts-new-wireless-indoor-e911-location-accuracy-requirements

[2] 3GPP TR 38.855 V16.0.0 (2019-03), 3rd Generation PartnershipProject; Technical Specification Group Radio Access Network; Study on NRpositioning support (Release 16)

[3] K. Doppler, E. Torkildson and J. Bouwen, “On wireless networks forthe era of mixed reality,” 2017 European Conference on Networks andCommunications (EuCNC), Oulu, 2017

[4] M. S. Elbamby, C. Perfecto, M. Bennis and K. Doppler, “TowardLow-Latency and Ultra-Reliable Virtual Reality,” in IEEE Network, vol.32, no. 2, pp. 78-84, March-April 2018.

[5] Mohammed S. Elbamby, Cristina Perfecto, Mehdi Bennis, and KlausDoppler, “Edge Computing Meets Millimeter-wave Enabled VR: Paving theWay to Cutting the Cord” [6] J. A. Del Peral-Rosado et al., “Survey ofCellular Mobile Radio Localization Methods: From 1G to 5G”, in IEEECommunications Surveys & Tutorials, vol. 20, no. 2, 2018

Integration of RAN localization and CV is described e.g. in:

[7] A. Alahi, A. Hague and L. Fei-Fei, “RGB-W: When Vision MeetsWireless,” 2015 IEEE International Conference on Computer Vision (ICCV),Santiago, 2015, pp. 3289-3297. doi: 10.1109/ICCV.2015.376RGB-W

[8] S. Papaioannou, A. Markham and N. Trigoni, “Tracking People inHighly Dynamic Industrial Environments,” in IEEE Transactions on MobileComputing, vol. 16, no. 8, pp. 2351-2365, 1 Aug. 2017.

doi: 10.1109/TMC.2016.2613523

[9] T. Ishihara, K. M. Kitani, C. Asakawa and M. Hirose, “DeepRadio-Visual Localization,” 2018 IEEE Winter Conference on Applicationsof Computer Vision (WACV), Lake Tahoe, NV, 2018, pp. 596-605.

doi: 10.1109/WACV.2018.00071

An exemplary computer vision technique that can be used to trackusers/objects of interest and calculate velocities based on depth imagesand time-series is disclosed in:

[10] J. Biswas and M. Veloso, “Depth camera based indoor mobile robotlocalization and navigation,” 2012 IEEE International Conference onRobotics and Automation, Saint Paul, Minn., 2012, pp. 1697-1702. doi:10.1109/ICRA.2012.6224766

[11] P. Viola and M. Jones, “Rapid object detection using a boostedcascade of simple features,” Proceedings of the 2001 IEEE ComputerSociety Conference on Computer Vision and Pattern Recognition. CVPR2001, Kauai, HI, USA, 2001, pp. I-I.

doi: 10.1109/CVPR.2001.990517

SUMMARY OF THE INVENTION

It is an object of the present invention to improve the prior art.

According to a first aspect of the invention, there is provided anapparatus, comprising means for providing configured to provide locationinformation indicating a location of a terminal to a radio-independentlocalization and tracking system; means for evaluating configured toevaluate at least one of environmental information and trackinginformation received from the radio-independent localization andtracking system with respect to the terminal in response to providingthe location information; means for managing configured to manage aresource for serving the terminal based on the at least one of theenvironmental information and the tracking information, wherein theenvironmental information comprises information about an environment ofthe terminal, and the tracking information comprises information about atrack of the terminal.

According to a second aspect of the invention, there is provided anapparatus, comprising means for identifying configured to identify anobject in a first representation of an environment of the object basedon location information received from a wireless network; means forgenerating configured to generate at least one of environmentalinformation and tracking information of the object from a secondrepresentation of the environment; means for providing configured toprovide the at least one of the environmental information and thetracking information to the wireless network in response to receivingthe location information, wherein the location information indicates alocation; the environmental information comprises information about theenvironment of the object, and the tracking information comprisesinformation about a track of the object.

According to a third object of the invention, there is provided anapparatus, comprising means for monitoring configured to monitor if arequest to measure a beam profile of a downlink receive beam isreceived; means for controlling configured to control, if the request isreceived, a means for setting and a means for measuring such that themeans for setting sets a direction of the downlink receive beam to atleast two different directions; and the means for measuring measures arespective channel state information for each of the at least twodifferent directions; means for reporting configured to report therespective channel state information for each of the at least twodifferent directions.

According to a fourth aspect of the invention, there is provided amethod, comprising providing location information indicating a locationof a terminal to a radio-independent localization and tracking system;evaluating at least one of environmental information and trackinginformation received from the radio-independent localization andtracking system with respect to the terminal in response to providingthe location information; managing a resource for serving the terminalbased on the at least one of the environmental information and thetracking information, wherein the environmental information comprisesinformation about an environment of the terminal, and the trackinginformation comprises information about a track of the terminal.

According to a fifth aspect of the invention, there is provided amethod, comprising identifying an object in a first representation of anenvironment of the object based on location information received from awireless network; generating at least one of environmental informationand tracking information of the object from a second representation ofthe environment; providing the at least one of the environmentalinformation and the tracking information to the wireless network inresponse to receiving the location information, wherein the locationinformation indicates a location; the environmental informationcomprises information about the environment of the object, and thetracking information comprises information about a track of the object.

According to a sixth aspect of the invention, there is provided amethod, comprising monitoring if a request to measure a beam profile ofa downlink receive beam is received; performing control, if the requestis received, such that a direction of the downlink receive beam is setto at least two different directions and a respective channel stateinformation is measured for each of the at least two differentdirections; reporting the respective channel state information for eachof the at least two different directions.

Each of the methods of the fourth to sixth aspects may be a method ofoptimizing resource allocation.

According to a seventh aspect of the invention, there is provided acomputer program product comprising a set of instructions which, whenexecuted on an apparatus, is configured to cause the apparatus to carryout the method according to any of the fourth to sixth aspects. Thecomputer program product may be embodied as a computer-readable mediumor directly loadable into a computer.

According to some embodiments of the invention, at least one of thefollowing advantages may be achieved:

-   -   Resource allocation in the wireless network may be improved;    -   Mobility in the wireless network may be improved;    -   Relatively small bandwidth requirements on the link between CV        system and the wireless network.

It is to be understood that any of the above modifications can beapplied singly or in combination to the respective aspects to which theyrefer, unless they are explicitly stated as excluding alternatives.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details, features, objects, and advantages are apparent from thefollowing detailed description of the preferred embodiments of thepresent invention which is to be taken in conjunction with the appendeddrawings, wherein:

FIG. 1 illustrates some example embodiments of the invention on a highlevel;

FIG. 2 shows a message exchange according to some example embodiments ofthe invention;

FIG. 3 shows an example embodiment of the invention;

FIG. 4 shows example associations between camera(s) of the CV system andantenna (array(s)) of the wireless network (wireless communicationnetwork);

FIG. 5 is a message flow according to some example embodiments of theinvention;

FIG. 6 shows an apparatus according to an embodiment of the invention;

FIG. 7 shows a method according to an embodiment of the invention;

FIG. 8 shows an apparatus according to an embodiment of the invention;

FIG. 9 shows a method according to an embodiment of the invention;

FIG. 10 shows an apparatus according to an embodiment of the invention;

FIG. 11 shows a method according to an embodiment of the invention; and

FIG. 12 shows an apparatus according to an embodiment of the invention.

DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS

Herein below, certain embodiments of the present invention are describedin detail with reference to the accompanying drawings, wherein thefeatures of the embodiments can be freely combined with each otherunless otherwise described. However, it is to be expressly understoodthat the description of certain embodiments is given by way of exampleonly, and that it is by no way intended to be understood as limiting theinvention to the disclosed details.

Moreover, it is to be understood that the apparatus is configured toperform the corresponding method, although in some cases only theapparatus or only the method are described.

Conventionally, information about the UE environment type (indoor,outdoor), direction, change of location etc. is only available to theRAN through radio measurements. On the other hand, a properly trainedcomputer vision solution can easily determine, for example, if aperson/device of interest has entered a train and will leave thestation. Based on this information, one may easily decide if it would bebetter to handover the UE to an on-board small-cell or to a sub-6 GHzmacro cell covering the entire train station area. Some exampleembodiments of this invention exploit this insight.

Furthermore, some example embodiments of this invention address theproblem how to minimize the impacts of lower availability of wirelesscommunication network. They complement the RRC/RRM using CV. Someexample embodiments of the invention track such transitions before radiomeasurement results become available by leveraging non-radio data suchas CV.

A sub-problem of practical interest is also addressed by some exampleembodiments of this invention—and to the best of the inventors'knowledge so far neglected by prior art: the identification and matchingof the RAN service area that will be analysed by the RAT-independentlocalization technique. In the present context, the term “matching”denotes what is known as spatiotemporal registration in the multi-sensorfusion community.

Some example embodiments of the invention provide a bi-directionalexchange of configuration, assistance, and event information between(one or multiple) radio network elements and (one or multiple) deviceswith computer-vision (CV) based localization and tracking capabilities.By means of dedicated signaling and interfaces the CV-based informationmay be used to augment the spatial awareness and performance of radioresource management (RRM) algorithms, more notably mobility and beammanagement algorithms.

FIG. 1 illustrates some example embodiments of the invention on a highlevel. In general, the CV system needs some spatial guidance to knowwhere (potentially swivelling) cameras should point to and which devicesto track and classify. The “configuration/exposure” arrow in Error!Reference source not found. illustrates that the wireless network (e.g.radio domain, more specifically: the localization agent) conveysassistance information to the CV system (the localization system in theCV system), such that the CV system understands the RAN service area tobe monitored. Namely, the wireless network may provide locationinformation to the CV such as angular information (azimuth, elevation, 3dB beamwidth) regarding beams serving one or more RRC connected devices(terminals (UEs)) or even the spatial coordinates (x,y, z, lat-long,etc) of one or more RRC connected devices obtained directly from thedevice via other radio-independent localization methods (e.g. GNSS) andconveyed to the network using features such as MDT signalling. Thus, CVmay generate tracking information of the one or more RRC connecteddevices such that the wireless network may benefit from the CV trackinginformation generated by CV.

If the CV system receives the location information from the wirelessnetwork, it may typically not detect the terminal (UE) at (or close to)that location but instead, it may detect an object, such as a humanbeing carrying the terminal or a car or a train, in which the terminalis located. The CV system may generate tracking information orenvironmental information for this object and the RAN may consider thisenvironmental information or tracking information as being related tothe terminal.

The CV system can detect (predict) a coming change how the wirelessnetwork may serve the terminal. For example, the CV system can detectthe geographical area where the wireless network may not be able toprovide the communication services at desired QoS. As another example,CV system may predict an unexpected high uplink load condition due topublic demonstration, or an obstacle blocking the beam-based coverage athigher frequencies above 6 GHz. The CV system can further provideinformation to the network about the geographical area and possibly theconstrains of blocking obstacles (environmental information). The CVsystem can also visually observe the number of UEs, UE waypoints, UEspeed, and mobility parameters (tracking information). The CV systemprovides such information to the wireless network (arrow“notifications/events”). Some of this information may be collected bythe wireless network, too, for example in MEC. The wireless network mayuse such information from CV system to optimize the wireless network(interaction between Localization agent/data and RRM algorithms). Inthis case the optimization algorithm in the wireless network (e.g. inMEC or gNB) may be triggered based on the CV system input.

In order to benefit from the environmental information and/or trackinginformation, the RAN needs to be able to understand the events detectedby the CV system. The CV system may signal previously configured orpredetermined events to the wireless network (e.g. RAN) through alocalization entity. Preferably, the localization entity resides asclose as possible to the air interface.

From a conceptual point of view, there may be three conceptual stages asfollows:

-   -   I. Rollout stage: Definition and physical/logical provisioning        of a communication interface between CV-enhanced RGB cameras and        RAN nodes (e.g. gNBs) to allow for the real-time exchange of        control signaling and data.    -   II. Preparation stage: RAN and CV define one or more devices        (e.g. connected UEs) of interest. The one or more devices are        defined based on their respective locations. The set may be        extendible. Preferably, a handshake protocol is used in this        stage. RAN and CV may additionally define a set of transition        events for the event stage. However, in some example        embodiments, RAN just informs CV on the events it wants to be        notified about.    -   III. Event stage: The CV-enhanced RGB cameras notifies gNB about        a transition in UE's state (tracking information) and/or about        the environment of the UE (such as position of obstacles near        the UE). The RRM (mobility) algorithms in the RAN make use of        this additional knowledge to optimize its decisions.

Since the CV system may fail or be corrupted, in some exampleembodiments, the output of the CV system augments the information usedfor RRM decisions and actions but does not drive them. In other words,the RAN may ignore the output of the CV system (such as reported events)if the RAN decides to do so. Some example embodiments of the inventiondo not use additional maps and/or real-time access to georeferencedand/or multi-layered data bases (e.g. radio environmental maps ordigital twins), while other example embodiments of the inventionintegrate one or more of such pieces of information.

Prior art documents [5]-[7] focus on the utilization of wirelesssolutions to improve the performance of positioning and people trackingsystems based on computer vision techniques. In contrast, according tosome example embodiments of the invention, the wireless network isimproved by means of the CV system. I.e., the intention of these exampleembodiments is opposite to that of the prior art [5] to [7]. As aconsequence, in the prior art RAN-related parameters are not exposed tothe CV-system, while according to some example embodiments of theinvention, RAN-related parameters (such as the location of the UEdetermined by RAN) are exposed to the CV system.

Hereinafter, an example embodiment is discussed at greater detail.

Some example embodiments of this invention exchange and utilizeinformation obtained from one or more CV systems for enhancing thespatial awareness capabilities of a wireless network. FIG. 2 shows amessage exchange according to some example embodiments of the invention.The flow is as follows:

-   -   1. CV including one or more cameras announces its presence and        provides constraint information to RAN (e.g. gNB or MEC). The        constraint information may comprise e.g. one or more of the        following: FoV, zoom, pan, and tilt constraints; coordinates,        height, elevation, and azimuth of the camera(s). Thus, the        constraint may define a two- or three-dimensional space which        may be monitored by the camera(s). CV may also indicate the        services (types of tracking information and environmental        information) it may offer.    -   2. RAN subscribes to a subset or all of the offered services.    -   3. CV acknowledges the subscription of message 2.    -   4. RAN sends respective IDs of one or more UEs for which        assistance from CV is desired to CV. The IDs may be conventional        IDs such as IMSI, or they may be specially generated IDs for the        communication between RAN and CV. In the latter case, the        specially generated IDs map 1:1 to the conventional IDs.        However, the mapping is known to RAN only but not to CV. Thus,        privacy may be preserved. In addition, RAN provides radio based        localization information of the UE(s) to CV. The localization        information may comprise e.g. respective estimated AoD based on        SSB beam or CSI-RS beam for each of the UEs for which assistance        is desired. It may comprise GNSS coordinates provided from the        UE to RAN.    -   5. CV acknowledges receipt of the UE ID(s) and related location        information.    -   6. CV starts tracking of the UEs. When an event according to the        subscribed services occurs, CV notifies RAN of the event. For        example, such an even may be that the UE enters a moving vehicle        or disappears behind an obstacle.    -   7. RRM in RAN takes the notification from RAN into account in        order to decide on resource allocation for the UE.

Messages/actions 6 and 7 may be continues until they are stopped by RANand/or CV system. In addition, some authentication and authorizationprocedures may be performed between RAN and CV, e.g. at or in betweeneach of the steps (not shown).

It is recommended that the message exchange of steps 1 to 6 isstandardized. However, it is not recommended to standardize the specificCV-algorithm performing the localization and tracking procedures (step6). It may serve as vendor differentiation mechanisms. An exemplaryalgorithm is found in [10] and the seminal work in [11]. The latter hasbeen extended countless time to track different features/objects ofinterest. However, the interface, the handshake and an extensiblelibrary of events to be reported requires proper standardization to makevisual and radio solutions from different vendors interoperable.

Some of the messages in FIG. 2 are optional. For example, messages 1 to3 correspond to the rollout stage I. Instead of a negotiation betweenRAN and CV, each of these systems may be configured separately with therespective parameters of the other system. Acknowledgments (messages 3and 5) may be omitted. Messages 4 and 5 correspond to the preparationstage II, and messages 6 and 7 correspond to the event stage IIIdescribed hereinabove.

FIG. 3 shows an example embodiment of the invention. A CV system with acamera is communicating with a wireless network. The CAM may beintegrated with the CV system (also called “smart CAM”, indicated by adashed line rectangle). However, a modular separation between the cameraand the CV intelligence is advantageous since the latter technologyevolves much faster than the former. The CV system may be connected toand/or integrated with more than one cameras. In the example embodiment,the CV system is connected to RAN (gNB) of the wireless network. Ingeneral, the CV system may be connected to other parts of the wirelessnetwork instead, such as CN or MEC. Bringing the interaction closer tothe air interface, i.e. to the gNB rather than to the CN, makes thesystem more responsive. The interaction is preferably limited to eventsand (extensible) assistance data, i.e. the video feed is not visible tothe RAN for privacy and complexity reasons. This interface allowspassing the signalling or the handshake procedure between the wirelessnetwork (preferably: RAN) and the CV system. It is recommended tostandardize the interface (defining objects/elements and signallingprocedure).

FIG. 4 illustrates some alternatives for the spatial correlation betweenthe (smart) cameras and the base stations (antenna arrays). These casesare strongly coupled with the network topology, so placement andconnections between “smart cameras” and network nodes should exploit thetypes of sites deployed to minimize infrastructure deployment costswhile maximizing the expected benefits.

The simplest case is a one-to-one mapping (FIG. 4a ), where the CVsolution is co-sited with a (macro) cellular tower so that the field ofview of a camera matches as much as possible the coverage of a cellsector. Another possibility is to have a camera on top of a tower,providing a visual localization/tracking to a multitude of small cells(many-to-one, FIG. 4b ) within the coverage area of the macro-cellhosting the visual system. FIG. 4c shows the option “many to one” whereplural cameras monitor the coverage area of one cell (e.g. of an omnicell). As a further option, a many-to-many configuration (FIG. 4d ) ispossible, too. In general, the camera(s) may be placed independentlyfrom the radio infrastructure, making several combinations andgeneralizations possible.

RAN and the CV system(s) exchange information for the matching andidentification of the region that will be analysed. This step will bepreferably performed at the roll-out stage the network, but it can alsobe done on-demand basis when the RAN subscribes to the services providedby the CV-system. Alternatively, the respective information may beconfigured separately in the respective other system.

For example, the CV will inform/advertise the RAN about the area coveredby its camera(s) and pertinent technical feature such as resolution,field of view (FOV), refresh rate, detection and mechanical andcomputerized tracking capabilities. Ensuring there is a match betweenthe coordinates used by the visual and radio systems is essential toguarantee the desired performance. Stereoscopic cameras may add depthinformation and can augment/facilitate the matching procedure. However,stereoscopic cameras are not required according to some exampleembodiments of the invention.

Because 5G NR is a system that heavily relies on beams which haveattributes such as elevation, azimuth and aperture which are used by RGBvideo cameras as well, the matching between the video map and the radiodomains can come naturally. Once again, the co-sited one to one mappingroll-out scenario depicted in FIG. 4a is the simplest one, especiallybecause the antennas and the camera may only differ with respect to thez coordinate and FOV. However, the geometrical conversions to and fromthe same spatial frame of reference is an implementation specific issue.It may be covered by the signalling exchanged during the roll-out stage.

Alternative and more complex approaches for the matching may include RFfingerprinting, the utilization of building vector data maps (BVDM)—thatmight be available for the same area—so that an even more accuratemapping becomes possible. This possibility will be discussed furthersubsequently, and it represents a step in the direction of having adigital twin of the area of interest which includes (real-time)knowledge about the RGB (visual) domain and radio domains.

In the second stage (preparation state II) a handshake protocol may beused between RAN and CV to trigger the tracking procedure for one ormultiple connected devices/users of interest. For example, this step maybe performed on the following occasions:

-   -   a. During RACH (transition to connected mode), in the case the        CV is already available;    -   b. Upon availability of CV, in the case the UE already existed        in the RAN yet no video feed was available for the area where        the UE has been moving prior to entering the visual field of the        particular CV system.

These occasions are not limiting. Also, the preparation step may beperformed for UEs having some sensitive traffic in order to reduce theload on the systems and interfaces.

The handshake may done by exploiting the matching (registration) setuppreviously. It can be done triggered from both gNB side and both CVside. An example embodiment is as follows:

The gNB signals the CV the existence of the active UE(s) of interest inthe areas known to be covered by the CV-system service. The RANshares/exposes a configurable fraction of the localization data (or allthe localization data) related to the devices of interest to assist thevisual tracking assistance, e.g. angular information (azimuth,elevation, 3 dB beamwidth, beam index), or even the spatial coordinates(x,y, z, lat-long, etc) obtained directly by the device(s) via otherradio-independent localization methods and which the device(s) conveyedto the RAN using features such as MDT signalling. Sharing thecoordinates greatly facilitates the tracking and classification of theconditions but raises privacy and security concerns and should be usedwhen the CV-system is a trusted computing platform.

The CV will then attempt to identify and track the UE(s). The CV caneither send already information regarding the UE, or just acknowledgethat the identification is performed. Frequently, the CV may notidentify the UE itself but an object (person, vehicle, train etc.)carrying the UE. In case the identification is unsuccessful, the CVsends an appropriate error notification to the gNB through dedicatedsignalling. Because the visual system can fail, in a preferredembodiment its outputs augment rather than drive the RRM decisions.

In the event stage III, several example embodiments are possible, andsome of them are described here:

-   -   a) The CV sends information about any change in the UE state to        the RAN, without being triggered by RAN:

Non-limiting examples of these changes can be:

-   -   i. Change in UE direction    -   ii. Change of environment indoors/outdoors    -   iii. Change in UE movement type:        pedestrian/vehicular/train/plane    -   iv. Etc: in front of a blockage, behind a blockage, etc    -   b) The gNB inquires for information regarding the UE location        when preparing for an event. A non-limiting example, is the        preparation of a HO: the gNB may ask for the environment type of        the UE and adapt the MRO parameters using the enhanced        intelligence provided by the CV system. The CV system replies        with the requested information.

In both cases, the CV sends environmental and/or tracking informationrelated to the UE to RAN.

In general, some example embodiments of the invention split theresponsibilities between the radio and the visual domain as follows:

-   -   RAN: Radio-based localization, utilization (for RRM purposes),        centralization and controllable exposure of information coming        from other localization techniques: REM, A-GNSS, Digital Twins    -   CV-System: Feature detection, structure from motion and        classification of conditions related to the received coordinates        and/or devices of interest.

As stated previously, the RAN may have full autonomy to heed or ignorethe events signaled by the CV-based system when taking actions. As anon-limiting exemplary use case, it may decide to neglectradio-domain-triggered handover events such as an intra-frequencyhandover event, in light of direction of movement and speed eventsextracted from motion by the visual system. For example, anintra-frequency handover event may be triggered when the signal from theserving cell becomes worse than threshold1 and the signal from theneighbor cell becomes better than threshold2. Both thresholds may betunable parameters (event “A5”).

In the following we describe an advanced use case at greater detail. Ittargets a ‘smart gNB’ concept. Note, ‘smart gNB’ denotes a gNB who hasdetailed knowledge of the environment and the most likely furtherevolution regarding its served cells so that an almost optimal PHY, MACand RRM layer processing becomes reality, which is conventionally notpossible just based on a few high level event reports. The umbrella ideais what has lately been called a mirror world and the fusion of multipledata sources. So far, it is open how to achieve the related accurateknowledge of the mirror world with reasonable overhead. Some exampleembodiments of the invention provide a solution to this problem:

-   -   A first consideration is regarding the camera to gNB (or cloud        like MEC, etc.) interface, which would generate huge data rates        if streamed constantly with high quality from the cameras to the        gNB. While such streaming might be possible if done over a high        capacity backbone network, it would have limitations in case of        e.g.        -   i) this connection includes a wireless link for example in            case of an integrated access and backhaul (IAB),        -   ii) there are latency requirements, which might suffer for            best effort IP traffic in case of overload situations,        -   iii) privacy concerns restrict the broad- or multicasting of            the camera data and/or add complex as well as latency.

In such cases it is not advisable to transmit the full camera streams.Therefore, in some example embodiments, the video feed itself is nottransmitted to the wireless network.

-   -   As described above, the CV might compress the camera video        streams and extract only most relevant information for the given        task to the ‘mirror world’.        -   assuming that a large part of the BVDM—defining the            environment—is more or less static, this part can be assumed            to be known at the CV as well as the gNB instance after some            initialization. It need not be transmitted during event            stage.        -   The moving objects inside the static BVDM as well as the            active mobile radio users together with their locations and            movements are relevant and may be reported from CV system to            the wireless network. As these moving objects can be other            persons (sitting, nomadic, fast moving), bikes, cars,            trucks, etc. these moving objects will have varying            capabilities with respect to speed, acceleration, rotation            capabilities, etc. For that reason, in some example            embodiments of the invention, these moving objects including            their capabilities are reported, as mentioned above.        -   It is assumed that ML algorithms are able to properly            classify these different types of moving objects. Over time            more classes might be defined between the CV and the gNB.        -   Moving objects with different capabilities then might be            reported adapted to their characteristics, for example with            different location update rates, with different moving or            rotating vectors for their future location prediction.        -   Depending on the scenario and the relative position of the            moving objects, these might have more or less impact to the            RF characteristics of the active users. Therefore, it makes            sense that the gNB informs the CV about relevant objects            and/or about more or less often location updates with more            or less accuracy.        -   Generally, a camera might cover areas with about 100 moving            objects (ignoring some extreme cases like concerts, etc.).            Providing 100 bit every 100 ms for each object would then            end up in a moderate data rate of about few kbits per camera            (instead of Mbits).    -   Another challenging task is the proper matching of a user        identified in the CV with that user (UE) in the mobile radio        system:        -   One natural option is to use accurate positioning based on            GNNS or other NR localization methods for the UE of interest            so that it can be mapped into the well known coordinates of            the BVDM (known at the gNB as well as the CV).        -   At the same time, for NR currently discussed position            accuracies might be not sufficient for a proper mapping, for            example in case the inaccuracy is in the range of more than            several tens of meter and one has to identify a person            within a cluster of multiple closeby persons. For that case            we propose an addition matching algorithm, for example            triggered by the gNB. This could be, for example, a specific            UE DL measurement, where the UE sweeps its Rx-beam over some            predefined—or from the gNB requested—beam angles, doing some            CSI measurements for each beam direction and reporting these            measurement results back to the gNB. The gNB can then map            the measured profile of measured beam CSI to the best            fitting person, as being identified as candidates by the CV            before. Alternatively, gNB may provide the measured profile            to CV which may then identify the best fitting person based            on the profile. As another option, super resolution            techniques identifying certain multi path component            parameters for certain multi TRP Tx signals may be used to            determine the location of the UE with high precision.

According to some example embodiments, the CV system is integrated withthe NR system (wireless network) using the MEC. The desired QoS forcertain UE velocities and/or UE locations may be lower than expected.The network may not be able to decide an optimal operation due to lackof measurements for example when a varying number of UEs are havingirregular data patterns. The CV system input to the network optimizationmay be routed using MEC processing and its output can be used toconfigure the relevant gNBs. The MEC requests the radio measurements andCV based information using an API where the request may include one ormore UE measurements and CV entities.

FIG. 5 shows a message flow according to some example embodiments of theinvention:

-   -   1. The MEC initiates the measurement collection for a set of        radio cells and CV systems associated to the radio cells.    -   2. MEC sends the Measurement Request and CV Request (i.e., the        request to provide data from the CV system such as tracking        information or environmental information) to the relevant gNBs        and CV system entities, respectively.    -   3. gNB sends a measurement configuration with the measurement        quantities to UEs. CV may indicated the UEs and/or from radio        measurements, one may derive that the UEs are located in the        vicinity of CV system. Optionally, gNB may indicate to the UE        the need for a location-based measurement.    -   4. UE sends a measurement report to gNB with the requested        measurement quantities and optionally its location.    -   5. gNB and CV forward the measurement and CV information reports        to MEC.    -   6. MEC processes the UE based radio measurements and CV        information.    -   7. MEC runs joint optimization of radio measurements and        CV-system information to the radio network parameters based on        the desired QoS.    -   8. MEC updates the parameters to gNBs, thus providing optimized        mobility parameters, for example.    -   9. gNB acknowledges the Update to MEC. The gNB can also reject        the update if the radio measurements are indicating the expected        performance wouldn't be met with the new CV-system augmented        configuration.

The gNB can update the UEs with the CV-system optimized parameters aspart of the normal RRC procedures, e.g. either triggering immediate RRCReconfiguration for UEs in RRC_CONNECTED state, during the next activedata transmission and reception, as part of the mobility procedures(handover), as part of the RAN Notification Area updates in RRC_INACTIVEstate, etc.

Some example embodiments of the invention provide a combination of CVand RRM where the CV gives a new dimension of insight to RRM. Forregistered users, the RAN is well aware of the UE location at cell levelin RRC_CONNECTED state, RAN notification area level in RRC_INACTIVE (RNAcan be a single cell), or tracking area level in RRC_IDLE. CV cancomplement this information.

In some example embodiments, RAN node utilizes UE's location informationand retrieves information from CV outside of radio access. RAN uses theCV based information, for example, to modify the UE's context, e.g.adding potential routing information and uses the modified UE's contextfor mobility optimization. The mobility optimization may include, forexample, cell prioritization during handover, prioritization of cellselection/reselection during low activity states (RRC_INACTIVE),preparation of conditional handover (CHO), or proactive push andpreparation of UE's context to another gNB. This neighboring gNB may beidentified according to CV input and complemented with radiomeasurements (or vice versa).

In a case where the user carrying the UE uses public transport, or in acity area, RAN determines passenger's UE position, mobility profile,speed and direction using CV positioning framework and whatever isavailable from RAN side, or RAT-independent methods such as GNSS. Forexample, the passenger enters the bus and CV detects this. When the busstarts to move along its route, the CV detects a change (UE→bus) andinforms the network about the UE's position and velocity (=direct impactto RRC, e.g. handovers, cell reselections, CHO preparation, cellprioritization, re-establishment target, . . . ). The network (e.g. gNB)gets real-time information from CV, potentially including real-timevehicle locations. The CV could even determine the bus line (e.g. busnumber) and, thus, what bus line the passenger is travelling. Therefore,network also knows bus line route, when connecting to externalinformation source. The network may get the CV information andprioritize a cell of another gNB (e.g. use “gNB2” instead of “gNB1”) inhandover decision. The benefit is reduced number of ping pong handoversbetween gNB1 and gNB2.

Another benefit from CV is that the RAN could predict (in this case CVmay be better than radio measurements) the next gNB (e.g. gNB2) andprepare the UE context to that gNB. In some example embodiments, eitherthe CV makes the decision or CV creates a triggering event whether theUE context will be pushed to the next gNB. This also reduces thelikelihood of UE Context fetch if the cell reselection was done inRRC_INACTIVE.

In other RRM or mobility optimization, the CV based location andtrajectory information can be used together with the RRC protocolinformation when low and/or high data activity UEs in RRC_INACTIVE andRRC_CONNECTED state are present in a CV enhanced location. Specific RNAmay be configured and signalled for the UEs whose UE Context or RRM isenhanced (in RAN) using this information. Since the RNA is notrepresenting the gNB deployment but the UEs predicted route (CV+RRM),the UEs may remain in low activity state during some part or the wholeroute without unnecessary RNA update procedures. Example RNA proceduresare indicated in 3GPP TS 38.300.

Advantages:

The mapping between the radio maps and the video feed are an importantstep in achieving the so-called “Universal Maps”, the multi spectral,multi-sensory contextual navigation of “MirrorWorld”.

Defining moving objects relative to a more static BVDM with differentcharacteristics as well as capabilities allows a suitably adaptedreporting per moving object, thereby minimizing the overall data ratefor the CV—gNB interface.

Triggering specific UE measurement and reporting modes—like a specificbeam sweeping—makes it possible to match candidate persons from the CVto active UEs from the RAN network.

The invention is an important enabler for ML for RAN as it allows thelabelling of the UE and provides further information for UE profiling.

The MEC can be located in the gNB-CU and in this case the latency andsignalling load would be minimized.

FIG. 6 shows an apparatus according to an embodiment of the invention.The apparatus may be a wireless network such as a RAN (represented by agNB, or eNB etc.), a core (represented e.g. by a MME), a MEC, or anelement thereof. FIG. 7 shows a method according to an embodiment of theinvention. The apparatus according to FIG. 6 may perform the method ofFIG. 7 but is not limited to this method. The method of FIG. 7 may beperformed by the apparatus of FIG. 6 but is not limited to beingperformed by this apparatus.

The apparatus comprises means for providing 10, means for evaluating 20,and means for managing 30. Each of the means for providing 10, means forevaluating 20, and means for managing 30 may be a providing means,evaluating means, and managing means, respectively. Each of the meansfor providing 10, means for evaluating 20, and means for managing 30 maybe a provider, evaluator, and manager, respectively. Each of the meansfor providing 10, means for evaluating 20, and means for managing 30 maybe a providing processor, evaluating processor, and managing processor,respectively.

The means for providing 10 provides location information to aradio-independent localization and tracking system (S10). The locationinformation indicates a location of a terminal (e.g. UE). Typically, themeans for providing 10 provides an identifier of the terminal along withthe location information.

The means for evaluating 20 evaluates at least one of environmentalinformation and tracking information (S20). The at least one of theenvironmental information and the tracking information is received fromthe radio-independent localization and tracking system with respect tothe terminal. It is received in response to providing the locationinformation. “Receiving in response” does not necessarily mean that theat least one of the environmental information and the trackinginformation is received immediately after the location information wasprovided. It means that the at least one of the environmentalinformation and the tracking information refers back to the providingmessage of S10, e.g. by reference to the identifier of the terminal, ifsuch identifier is provided. The environmental information comprisesinformation about an environment of the terminal, and the trackinginformation comprises information about a track of the terminal.

The means for managing 30 manages a resource for serving the terminalbased on the at least one of the environmental information and thetracking information (S30). The resource may be a resource of the radionetwork or of the core network or a combination thereof.

FIG. 8 shows an apparatus according to an embodiment of the invention.The apparatus may be a computer vision system or an element thereof.FIG. 9 shows a method according to an embodiment of the invention. Theapparatus according to FIG. 8 may perform the method of FIG. 9 but isnot limited to this method. The method of FIG. 9 may be performed by theapparatus of FIG. 8 but is not limited to being performed by thisapparatus.

The apparatus comprises means for identifying 110, means for generating120, and means for providing 130. Each of the means for identifying 110,means for generating 120, and means for providing 130 may be anidentifying means, generating means, and providing means, respectively.Each of the means for identifying 110, means for generating 120, andmeans for providing 130 may be an identifier, generator, and provider,respectively. Each of the means for identifying 110, means forgenerating 120, and means for providing 130 may be an identifyingprocessor, generating processor, and providing processor, respectively.

The means for identifying 110 identifies an object in a firstrepresentation of an environment (e.g. a first image) of an object basedon location information (S110). The location information indicates alocation, It is received from a wireless network.

The means for generating 120 generates at least one of environmentalinformation and tracking information of the object from a secondrepresentation of the environment (e.g. a second image) (S120). Thesecond representation of the environment may be the same representationof the environment as the first representation of the environment, orthe second representation of the environment may be different from thefirst representation of the environment. The means for generating mayuse one, two, or more than two representations of the environment. Theenvironmental information comprises information about the environment ofthe object, and the tracking information comprises information about atrack of the object.

The means for providing 130 provides the at least one of theenvironmental information and the tracking information to the wirelessnetwork (S130). In particular, the means for providing 130 provides theat least one of the environmental information and the trackinginformation in response to receiving the location information.“Providing in response” does not necessarily mean that the at least oneof the environmental information and the tracking information isprovided immediately after the location information was received. Itmeans that the at least one of the environmental information and thetracking information refers back to the providing message of S110comprising the location information, e.g. by reference to an identifierof a terminal, if such identifier is provided.

FIG. 10 shows an apparatus according to an embodiment of the invention.The apparatus may be a terminal (such as a UE) or an element thereof.FIG. 11 shows a method according to an embodiment of the invention. Theapparatus according to FIG. 10 may perform the method of FIG. 11 but isnot limited to this method. The method of FIG. 11 may be performed bythe apparatus of FIG. 10 but is not limited to being performed by thisapparatus.

The apparatus comprises means for monitoring 210, means for controlling220, and means for reporting 230. Each of the means for monitoring 210,means for controlling 220, and means for reporting 230 may be amonitoring means, controlling means, and reporting means, respectively.Each of the means for monitoring 210, means for controlling 220, andmeans for reporting 230 may be a monitor, controller, and reporter,respectively. Each of the means for monitoring 210, means forcontrolling 220, and means for reporting 230 may be a monitoringprocessor, controlling processor, and reporting processor, respectively.

The means for monitoring 210 monitors if a request to measure a beamprofile of a downlink receive beam is received (S210).

If the request is received (S210=yes), the means for controlling 220controls a means for setting and a means for measuring such that thebeam profile is measured (S220). Namely, it controls the means forsetting such that the means for setting sets a direction of the downlinkreceive beam to at least two different directions; and it controls themeans for measuring such that it measures a respective channel stateinformation for each of the at least two different directions.

The means for reporting 230 reports the respective channel stateinformation for each of the at least two different directions (S230).

FIG. 12 shows an apparatus according to an embodiment of the invention.The apparatus comprises at least one processor 810, at least one memory820 including computer program code, and the at least one processor 810,with the at least one memory 820 and the computer program code, beingarranged to cause the apparatus to at least perform at least one of themethods according to FIGS. 7, 9, and 11.

Embodiments of the invention are described for 3GPP networks such as 3Gnetworks, 4G networks, 5G networks. However, the invention is notrestricted to 3GPP networks and may be employed in other wirelessnetworks, too.

A UE is an example of a terminal. However, the terminal may be anydevice capable to connect to the (3GPP) radio network such as a MTCdevice, a loT device etc. The invention is described substantially forUEs in RRC connected state. However, the invention is not limited tosuch UEs. It may be applied to UEs in RRC inactive stat or in idle mode,too, if corresponding signalling is defined.

A gNB is an example of a base station. However, the base station may beany device capable to provide a base station function in the respectiveradio network, such as a eNB or a NodeB.

The invention is described with a focus on allocating and/or optimizingradio resources for the terminal. However, the invention is not limitedto radio resources. It may be used for allocating and/or optimizing coreresources, too. For example, based on the tracking information from theCV system, core may decide whether or not an inter-MME handover ispreferred.

The position of the UE may be determined by CN based LMF or RAN basedLMC or a combination of both. Typically, LMF and/or LMC are able tocontrol the UE based or UE assisted positioning procedures. Thepositioning method may be selected based on the UE capability and/ornetwork support, e.g. the method is not limited to OTDOA, for example.

The invention is described with respect to a RGB camera. However,another camera for obtaining a visual image may be used instead of theRGB camera.

The invention is not limited to visual images and CV systems. Forexample, the invention may be applied to infrared images, too. Theinvention is not even limited to images obtained by electromagneticradiation. For example, it may be applied to signals from ultrasonicreflection (echoes), too. The invention may be applied to an arbitrarycombination of such images and signals. Each of these images and signalsmay be a representation of the environment of the object. A CV system isa particular kind of a radio-independent localization and trackingsystem. Here “radio-independent” means independent from the informationderivable from the radio measurements in the wireless network.

One piece of information may be transmitted in one or plural messagesfrom one entity to another entity. Each of these messages may comprisefurther (different) pieces of information.

Names of network elements, protocols, and methods are based on currentstandards. In other versions or other technologies, the names of thesenetwork elements and/or protocols and/or methods may be different, aslong as they provide a corresponding functionality.

If not otherwise stated or otherwise made clear from the context, thestatement that two entities are different means that they performdifferent functions. It does not necessarily mean that they are based ondifferent hardware. That is, each of the entities described in thepresent description may be based on a different hardware, or some or allof the entities may be based on the same hardware. It does notnecessarily mean that they are based on different software. That is,each of the entities described in the present description may be basedon different software, or some or all of the entities may be based onthe same software. Each of the entities described in the presentdescription may be embodied in the cloud.

According to the above description, it should thus be apparent thatexample embodiments of the present invention provide, for example, awireless network represented by a base station such as a gNB or eNB orby a MEC, or a component thereof, an apparatus embodying the same, amethod for controlling and/or operating the same, and computerprogram(s) controlling and/or operating the same as well as mediumscarrying such computer program(s) and forming computer programproduct(s). According to the above description, it should thus beapparent that example embodiments of the present invention provide, forexample, a computer vision system, or a component thereof, an apparatusembodying the same, a method for controlling and/or operating the same,and computer program(s) controlling and/or operating the same as well asmediums carrying such computer program(s) and forming computer programproduct(s). According to the above description, it should thus beapparent that example embodiments of the present invention provide, forexample, a terminal such as a UE, or a component thereof, an apparatusembodying the same, a method for controlling and/or operating the same,and computer program(s) controlling and/or operating the same as well asmediums carrying such computer program(s) and forming computer programproduct(s).

Implementations of any of the above described blocks, apparatuses,systems, techniques or methods include, as non-limiting examples,implementations as hardware, software, firmware, special purposecircuits or logic, general purpose hardware or controller or othercomputing devices, or some combination thereof.

It is to be understood that what is described above is what is presentlyconsidered the preferred embodiments of the present invention. However,it should be noted that the description of the preferred embodiments isgiven by way of example only and that various modifications may be madewithout departing from the scope of the invention as defined by theappended claims.

1. Wireless network apparatus, comprising: at least one processor; andat least one non-transitory memory including computer program code, theat least one memory and the computer program code configured to, withthe at least one processor, cause the wireless network apparatus to:provide location information indicating a location of a terminal to aradio-independent localization and tracking system; receive at least oneof environmental information or tracking information from theradio-independent localization and tracking system in response toproviding the location information; evaluate the received at least oneof environmental information or tracking information; manage a resourcefor serving the terminal based on the at least one of the environmentalinformation or the tracking information, wherein the environmentalinformation comprises information about an environment of the terminal,and the tracking information comprises information about a track of theterminal.
 2. The wireless network apparatus according to claim 1,wherein the at least one memory and the computer program code areconfigured to, with the at least one processor, cause the wirelessnetwork apparatus to: obtain constraint information indicating aconstraint of the radio-independent localization and tracking system forgenerating any tracking information; check, based on the constraintinformation, when the radio-independent localization and tracking systemis capable to obtain the at least one of the environmental informationor the tracking information with respect to the terminal; inhibit theproviding from providing the location information of the terminal to theradio-independent localization and tracking system when theradio-independent localization and tracking system is not capable toobtain the at least one of the environmental information or the trackinginformation with respect to the terminal.
 3. The wireless networkapparatus according to claim 2, wherein the constraint informationcomprises an indication of a space monitored by the radio-independentlocalization and tracking system.
 4. The apparatus according to claim 1,wherein the at least one memory and the computer program code areconfigured to, with the at least one processor, cause the wirelessnetwork apparatus to: monitor when a predefined event related to theterminal occurs; request the at least one of the environmentalinformation or the tracking information from the radio-independentlocalization and tracking system when the predefined event occurs. 5.The wireless network apparatus according to claim 4, wherein thepredefined event comprises at least one of a request for a handover ofthe terminal or a request for a beam reselection of the terminal.
 6. Thewireless network apparatus according to claim 5, wherein the at leastone memory and the computer program code are configured to, with the atleast one processor, cause the wireless network apparatus to: supervisewhen the at least one of the environmental information or the trackinginformation is received from the radio-independent localization andtracking system; trigger the means for evaluating to evaluate the atleast one of the environmental information or the tracking informationwhen the at least one of the environmental information or the trackinginformation is received.
 7. The wireless network apparatus according toclaim 6, wherein the at least one memory and the computer program codeare configured to, with the at least one processor, cause the wirelessnetwork apparatus to: determine the location of the terminal based on atleast one of an evaluation of a radio measurement or an evaluation of asatellite measurement.
 8. The wireless network apparatus according toclaim 7, wherein the radio measurement comprises a measurement of aprofile of a downlink receive beam received from the terminal. 9.-12.(canceled)
 13. Radio-independent localization tracking systemcomprising: at least one processor; and at least one non-transitorymemory including computer program code, the at least one memory and thecomputer program code configured to, with the at least one processor,cause the radio-independent localization tracking system to: receivelocation information from a wireless network; identify an object in afirst representation of an environment of the object based on thereceived location information received from a wireless network; generateat least one of environmental information or tracking information of theobject from a second representation of the environment; provide the atleast one of the environmental information or the tracking informationto the wireless network in response to receiving the locationinformation, wherein the location information indicates a location of aterminal; and wherein the environmental information comprisesinformation about the environment of the object, and the trackinginformation comprises information about a track of the object.
 14. Theradio-independent localization tracking system according to claim 13,wherein the at least one memory and the computer program code areconfigured to, with the at least one processor, cause the wirelessnetwork radio-independent localization tracking system to: inform thewireless network on a constraint information indicating a constraint forgenerating any environmental information or tracking information. 15.The radio-independent localization tracking system according to claim14, wherein the constraint information comprises an indication of amonitored space.
 16. The radio-independent localization tracking systemaccording to claim 13, wherein the at least one memory and the computerprogram code are configured to, with the at least one processor, causethe wireless network radio-independent localization tracking system to:supervise when a request to provide the at least one of theenvironmental information or the tracking information is received fromthe wireless network; trigger the providing to provide the at least oneof the environmental information or the tracking information when therequest is received. 17.-22. (canceled)
 23. Method executed by awireless network apparatus comprising steps of: providing locationinformation indicating a location of a terminal to a radio-independentlocalization and tracking system; evaluating at least one ofenvironmental information or tracking information received from theradio-independent localization and tracking system with respect to theterminal in response to providing the location information; managing aresource for serving the terminal based on the at least one of theenvironmental information or the tracking information, wherein theenvironmental information comprises information about an environment ofthe terminal, and the tracking information comprises information about atrack of the terminal.
 24. The method according to claim 23, furthercomprising obtaining constraint information indicating a constraint ofthe radio-independent localization and tracking system for generatingany tracking information; checking, based on the constraint information,when the radio-independent localization and tracking system is capableto obtain the at least one of the environmental information or thetracking information with respect to the terminal; inhibiting theproviding of the location information of the terminal to theradio-independent localization and tracking system when theradio-independent localization and tracking system is not capable toobtain the at least one of the environmental information or the trackinginformation with respect to the terminal.
 25. The method according toclaim 24, wherein the constraint information comprises an indication ofa space monitored by the radio-independent localization and trackingsystem.
 26. The method according to claim 23, further comprising:monitoring when a predefined event related to the terminal occurs;requesting the at least one of the environmental information or thetracking information from the radio-independent localization andtracking system when the predefined event occurs.
 27. The methodaccording to claim 26, wherein the predefined event comprises at leastone of a request for a handover of the terminal or a request for a beamreselection of the terminal.
 28. The method according to claim 23,further comprising: supervising when the at least one of theenvironmental information or the tracking information is received fromthe radio-independent localization and tracking system; triggering theevaluating of the at least one of the environmental information or thetracking information when the at least one of the environmentalinformation or the tracking information is received.
 29. The methodaccording to claim 23, further comprising: determining configured todetermine the location of the terminal based on at least one of anevaluation of a radio measurement or an evaluation of a satellitemeasurement.
 30. The method according to claim 29, wherein the radiomeasurement comprises a measurement of a profile of a downlink receivebeam received from the terminal. 31.-46. (canceled)
 47. A non-transitoryprogram storage device readable by a machine, tangibly embodying aprogram of instructions executable by the machine for performingoperations, the operations comprising the method as claimed in claim 23.